Biometrics, the science of using physical traits to identify individuals, is playing an increasing role in our security-conscious society and across the globe. Biometric authentication, or bioauthentication, systems are being used to secure everything from amusement parks to bank accounts to military installations. Yet developments in this field have not been matched by an equivalent improvement in the statistical methods for evaluating these systems. Compensating for this need, this unique text/reference provides a basic statistical methodology for practitioners and testers of bioauthentication devices, supplying a set of rigorous statistical methods for evaluating biometric authentication systems. This framework of methods can be extended and generalized for a wide range of applications and tests. This is the first single resource on statistical methods for estimation and comparison of the performance of biometric authentication systems. The book focuses on six common performance metrics: for each metric, statistical methods are derived for a single system that incorporates confidence intervals, hypothesis tests, sample size calculations, power calculations and prediction intervals. These methods are also extended to allow for the statistical comparison and evaluation of multiple systems for both independent and paired data. Topics and features: * Provides a statistical methodology for the most common biometric performance metrics: failure to enroll (FTE), failure to acquire (FTA), false non-match rate (FNMR), false match rate (FMR), and receiver operating characteristic (ROC) curves * Presents methods for the comparison of two or more biometric performance metrics * Introduces a new bootstrap methodology for FMR and ROC curve estimation * Supplies more than 120 examples, using publicly available biometric data where possible * Discusses the addition of prediction intervals to the bioauthentication statistical toolset * Describes sample-size and power calculations for FTE, FTA, FNMR and FMR Researchers, managers and decisions makers needing to compare biometric systems across a variety of metrics will find within this reference an invaluable set of statistical tools. Written for an upper-level undergraduate or master's level audience with a quantitative background, readers are also expected to have an understanding of the topics in a typical undergraduate statistics course. Dr. Michael E. Schuckers is Associate Professor of Statistics at St. Lawrence University, Canton, NY, and a member of the Center for Identification Technology Research.

This book and its sister volume collect refereed papers presented at the 7th Inter- tional Symposium on Neural Networks (ISNN 2010), held in Shanghai, China, June 6-9, 2010. Building on the success of the previous six successive ISNN symposiums, ISNN has become a well-established series of popular and high-quality conferences on neural computation and its applications. ISNN aims at providing a platform for scientists, researchers, engineers, as well as students to gather together to present and discuss the latest progresses in neural networks, and applications in diverse areas. Nowadays, the field of neural networks has been fostered far beyond the traditional artificial neural networks. This year, ISNN 2010 received 591 submissions from more than 40 countries and regions. Based on rigorous reviews, 170 papers were selected for publication in the proceedings. The papers collected in the proceedings cover a broad spectrum of fields, ranging from neurophysiological experiments, neural modeling to extensions and applications of neural networks. We have organized the papers into two volumes based on their topics. The first volume, entitled "Advances in Neural Networks- ISNN 2010, Part 1," covers the following topics: neurophysiological foundation, theory and models, learning and inference, neurodynamics. The second volume en- tled "Advance in Neural Networks ISNN 2010, Part 2" covers the following five topics: SVM and kernel methods, vision and image, data mining and text analysis, BCI and brain imaging, and applications.

This book and its sister volume collect refereed papers presented at the 7th Inter- tional Symposium on Neural Networks (ISNN 2010), held in Shanghai, China, June 6-9, 2010. Building on the success of the previous six successive ISNN symposiums, ISNN has become a well-established series of popular and high-quality conferences on neural computation and its applications. ISNN aims at providing a platform for scientists, researchers, engineers, as well as students to gather together to present and discuss the latest progresses in neural networks, and applications in diverse areas. Nowadays, the field of neural networks has been fostered far beyond the traditional artificial neural networks. This year, ISNN 2010 received 591 submissions from more than 40 countries and regions. Based on rigorous reviews, 170 papers were selected for publication in the proceedings. The papers collected in the proceedings cover a broad spectrum of fields, ranging from neurophysiological experiments, neural modeling to extensions and applications of neural networks. We have organized the papers into two volumes based on their topics. The first volume, entitled "Advances in Neural Networks- ISNN 2010, Part 1," covers the following topics: neurophysiological foundation, theory and models, learning and inference, neurodynamics. The second volume en- tled "Advance in Neural Networks ISNN 2010, Part 2" covers the following five topics: SVM and kernel methods, vision and image, data mining and text analysis, BCI and brain imaging, and applications.

This volume contains the papers presented at the 23rd Canadian Conference on Arti?cial Intelligence (AI 2010). The conference was held in Ottawa, Ontario, fromMay31toJune2,2010,andwascollocatedwiththe36thGraphicsInterface Conference(GI2010),andthe7thCanadianConferenceonComputerandRobot Vision (CRV 2010). The Program Committee received 90 submissions for the main conference, AI2010,fromacrossCanadaandaroundtheworld.Eachsubmissionwasreviewed byuptofourreviewers.Forthe?nalconferenceprogramandforinclusioninthese proceedings, 22 regular papers, with allocation of 12 pages each, were selected. Additionally,26 shortpapers,with allocationof 4 pageseach,wereaccepted. The papers from the Graduate Student Symposium are also included in the proceedings:sixoral(fourpages)andsixposter(twopages)presentationpapers. The conference programfeatured three keynote presentations by Dekang Lin (Google Inc.), Guy Lapalme (Universit'edeMontr' eal), and Evangelos Milios (Dalhousie University). The one-page abstracts of their talks are also included in the proceedings. Two pre-conference workshops, each with their own proceedings, were held on May 30, 2010. The Workshop on Intelligent Methods for Protecting Privacy and Con?dentiality in Data was organized by Khaled El Emam and Marina Sokolova. The workshop on Teaching AI in Computing and Information Te- nology (AI-CIT 2010) was organized by Danny Silver, Leila Kosseim, and Sajid Hussain. This conference wouldnot havebeen possible without the hardworkofmany people.WewouldliketothankallProgramCommitteemembersandexternal- viewers for their e?ort in providing high-quality reviews in a timely manner. We thank all the authors of submitted papers for submitting their work,and the - thors of selected papers for their collaboration in preparation of the ?nal copy. ManythankstoEbrahimBagheriandMarinaSokolovafororganizingtheGra- ateStudentSymposium,andchairingtheProgramCommitteeofthesymposium. We are in debt to Andrei Voronkov for developing the EasyChair conference managementsystemandmakingitfreelyavailabletotheacademicworld.Itisan amazinglyelegantand functionalWeb-basedsystem,whichsavedus muchtime.

These proceedings containall the papers that werepresented at the 4th Inter- tional Conference on Language and Automata Theory and Applications (LATA 2010), held in Trier, Germany, during May 24-28, 2010. The scope of LATA is rather broad, including: algebraic language theory; algorithms on automata and words; automata and logic; automata for system analysis and program veri?cation; automata, concurrency and Petri nets; cel- lar automata; combinatorics on words; computability; computational compl- ity; computer linguistics; data and image compression; decidability questions on words and languages; descriptional complexity; DNA and other models of bio-inspired computing; document engineering; foundations of ?nite state te- nology; fuzzy and rough languages; grammars (Chomsky hierarchy, contextual, multidimensional, uni?cation, categorial, etc. ); grammars and automata arc- tectures; grammatical inference and algorithmic learning; graphs and graph transformation; language varieties and semigroups; language-based cryptog- phy; language-theoretic foundations of arti?cial intelligence and arti?cial life; neuralnetworks;parallelandregulatedrewriting;parsing;patternmatching and pattern recognition; patterns and codes; power series; quantum, chemical and optical computing; semantics; string and combinatorial issues in computational biology and bioinformatics; symbolic dynamics; term rewriting; text algorithms; textretrieval;transducers;trees, treelanguagesandtreemachines;andweighted machines. LATA 2010 received 115 submissions, many among them of good quality. Each one was reviewed by at least three Program Committee members plus, in mostcases, byadditionalexternalreferees. Afterathoroughandvividdiscussion phase, the committee decided to accept 47 papers (which means an acceptance rate of 40. 86%). The conference program also included four invited talk

This book is the first attempt to bring together current research findings in the domain of interactive horizontal displays. The novel compilation will integrate and summarise findings from the most important international tabletop research teams. It will provide a state-of-the art overview of this research domain and therefore allow for discussion of emerging and future directions in research and technology of interactive horizontal displays.

Latest advances in interaction and software technologies and their increasing availability beyond research labs, refuels the interest in interactive horizontal displays. In the early 1990s Mark Weiser s vision of Ubiquitous Computing redefined the notion of Human Computer Interaction. Interaction was no longer considered to happen only with standard desktop computers but also with elements of their environment.

This book is structured in three major areas: under, on/above and around tabletops. These areas are associated with different research disciplines such as Hardware/Software and Computer Science, Human Computer Interaction (HCI) and Computer Supported Collaborative Work (CSCW). However, the comprehensive and compelling presentation of the topic of the book results from its interdisciplinary character. The book addresses fellow researchers who are interested in this domain and practitioners considering interactive tabletops in real-world projects. It will also be a useful introduction into tabletop research that can be used for the academic curriculum."

It is indeed a great pleasure to welcome you to the proceedings of the Inter- tional Symposium "Computational Modeling of Objects Represented in Images. Fundamentals,MethodsandApplications"(CompIMAGE2010)heldinBu?alo, NY, May 5-7, 2010. This was the second issue of CompIMAGE symposia, the ?rst one being held in Coimbra, Portugal. The purpose of CompIMAGE 2010 was to provide a common forum for - searchers, scientists, engineers, and practitioners around the world to present their latest research ?ndings, ideas, developments, and applications in the area of computational modeling of objects represented in images. In particular, the symposium aimed to attract scientists who use various approaches - such as ?nite element method, optimization methods, modal analysis, stochastic me- ods, principal components analysis, independent components analysis, distri- tion models, geometrical modeling, digital geometry, grammars,fuzzy logic, and others - to solve problems that appear in a wide range of areas as diverse as medicine, robotics, defense, security, astronomy,materialscience, and manuf- turing. CompIMAGE 2010 was highly international. Its Program Committee m- bersarerenownedexpertscomingfrom25di?erentcountries.Submissionstothe symposium came from 22 countries from Africa, Asia, Europe, North and South America. Overall, representatives of 32 countries contributed to the symposium in di?erent capacities.

The International Gesture Workshops (GW) are interdisciplinary events for those researching gesture-based communication across the disciplines. The focus of these events is a shared interest in understanding gestures and sign language in their many facets, and using them for advancing human-machine interaction. Since 1996, International Gesture Workshops have been held roughly every second year, with fully reviewed proceedings published by Springer. The International Gesture Workshop GW 2009 was hosted by Bielefeld University's Center for Interdisciplinary Research (ZiF - Zentrum fur interdisziplinare Forschung) during February 25-27, 2009. Like its predecessors, GW 2009 aimed to provide a platform for participants to share, discuss, and criticize recent and novel research with a multidisciplinary audience. More than 70 computer scientists, linguistics, psychologists, neuroscientists as well as dance and music scientists from 16 countries met to present and exchange their newest results under the umbrella theme "Gesture in Embodied Communication and Human-Computer Interaction. " Consistent with the steady growth of research activity in this area, a large number of high-quality submissions were received, which made GW 2009 an exciting and important event for anyone interested in gesture-related technological research relevant to human-computer interaction. In line with the practice of previous gesture workshops, presenters were invited to submit theirs papers for publication in a subsequent peer-reviewed publication of high quality. The present book is the outcome of this effort. Representing the research work from eight countries, it contains a selection of 28 thoroughly reviewed articles.

It givesus greatpleasureto presentthe proceedings of the 9th Asian Conference on Computer Vision (ACCV 2009), held in Xi'an, China, in September 2009. This was the ?rst ACCV conference to take place in mainland China. We received a total of 670 full submissions, which is a new record in the ACCV series. Overall, 35 papers were selected for oral presentation and 131 as posters, yielding acceptance rates of 5.2% for oral, 19.6% for poster, and 24.8% in total. In the paper reviewing, we continued the tradition of previous ACCVsbyconductingtheprocessinadouble-blindmanner.Eachofthe33Area Chairs received a pool of about 20 papers and nominated a number of potential reviewers for each paper. Then, Program Committee Chairs allocated at least three reviewers to each paper, taking into consideration any con?icts of interest and the balance of loads. Once the reviews were ?nished, the Area Chairs made summaryreportsforthepapersintheirpools, basedonthereviewers'comments and on their own assessments of the papers.

Why are We Writing This Book? Visual data (graphical, image, video, and visualized data) affect every aspect of modern society. The cheap collection, storage, and transmission of vast amounts of visual data have revolutionized the practice of science, technology, and business. Innovations from various disciplines have been developed and applied to the task of designing intelligent machines that can automatically detect and exploit useful regularities (patterns) in visual data. One such approach to machine intelligence is statistical learning and pattern analysis for visual data. Over the past two decades, rapid advances have been made throughout the ?eld of visual pattern analysis. Some fundamental problems, including perceptual gro- ing,imagesegmentation, stereomatching, objectdetectionandrecognition,and- tion analysis and visual tracking, have become hot research topics and test beds in multiple areas of specialization, including mathematics, neuron-biometry, and c- nition. A great diversity of models and algorithms stemming from these disciplines has been proposed. To address the issues of ill-posed problems and uncertainties in visual pattern modeling and computing, researchers have developed rich toolkits based on pattern analysis theory, harmonic analysis and partial differential eq- tions, geometry and group theory, graph matching, and graph grammars. Among these technologies involved in intelligent visual information processing, statistical learning and pattern analysis is undoubtedly the most popular and imp- tant approach, and it is also one of the most rapidly developing ?elds, with many achievements in recent years. Above all, it provides a unifying theoretical fra- work for intelligent visual information processing applications.

This volume contains extended papers from Sensor-KDD 2008, the Second - ternational Workshop on Knowledge Discovery from Sensor Data. The second Sensor-KDDworkshopwasheldinLasVegasonAugust24,2008, inconjunction with the 14th ACM SIGKDD InternationalConference on KnowledgeDiscovery and Data Mining. Wide-area sensor infrastructures, remote sensors, and wireless sensor n- works, RFIDs, yield massive volumes of disparate, dynamic, and geographically distributeddata.Assuchsensorsarebecomingubiquitous, asetofbroadrequi- ments is beginning to emerge across high-priority applications including dis- ter preparedness and management, adaptability to climate change, national or homelandsecurity, andthe managementofcriticalinfrastructures.Therawdata from sensors need to be e?ciently managed and transformed to usable infor- tion through data fusion, which in turn must be converted to predictive insights via knowledge discovery, ultimately facilitating automated or human-induced tactical decisions or strategic policy based on decision sciences and decision s- port systems. The expected ubiquity of sensors in the near future, combined with the cr- ical roles they are expected to play in high-priority application solutions, points to an era of unprecedented growth and opportunities. The main motivation for the Sensor-KDD series of workshops stems from the increasing need for a forum to exchange ideas and recent research results, and to facilitate coll- oration and dialog between academia, government, and industrial stakeho- ers. This is clearly re?ected in the successful organization of the ?rst workshop (http: //www.ornl.gov/sci/knowledgediscovery/SensorKDD-2007/)alongwiththe ACMKDD-2007conference, whichwasattendedbymorethanseventyregistered participants, and resulted in an edited book (CRC Press, ISBN-9781420082326, 2008), and a special issue in the Intelligent Data Analysis journal (Volume 13, Number 3, 2

This book introduces a new way to analyze multivariate data. The analysis of data based on multivariate spatial signs and ranks proceeds very much as does a tra- tional multivariate analysis relying on the assumption of multivariate normality: the L norm is just replaced by different L norms, observation vectors are replaced by 2 1 their(standardizedandcentered)spatial signsandranks, andso on.Themethodsare fairly ef?cient and robust, and no moment assumptions are needed. A uni?ed t- ory starting with the simple one-sample location problem and proceeding through the several-sample location problems to the general multivariate linear regression model and ?nally to the analysis of cluster-dependent data is presented. The material is divided into 14 chapters. Chapter 1 serves as a short introd- tion to the general ideas and strategies followed in the book. Chapter 2 introduces and discusses different types of parametric, nonparametric, and semiparametric s- tistical models used to analyze the multivariate data. Chapter 3 provides general descriptive tools to describe the properties of multivariate distributions and mul- variate datasets. Multivariate location and scatter functionals and statistics and their use is described in detail. Chapter 4 introduces the concepts of multivariate spatial sign, signed-rank, andrank, and shows their connectionto certain L objectivefunc- 1 tions. Also sign and rank covariance matrices are discussed carefully. The ?rst four chapters thus provide the necessary tools to understand the remaining part of the b

In den letzten Jahren hat sich der Workshop "Bildverarbeitung fur die Medizin" durch erfolgreiche Veranstaltungen etabliert. Ziel ist auch 2010 wieder die Darstellung aktueller Forschungsergebnisse und die Vertiefung der Gesprache zwischen Wissenschaftlern, Industrie und Anwendern. Die Beitrage dieses Bandes - einige in englischer Sprache - behandeln alle Bereiche der medizinischen Bildverarbeitung, insbesondere Bildgebung, CAD, Segmentierung, Bildanalyse, Visualisierung und Animation, Roboter und Manipulatoren, Chirurgische Simulatoren, Diagnose, Therapieplanung sowie deren klinische Anwendungen.

Metaheuristicscontinuetodemonstratetheire?ectivenessforanever-broadening range of di?cult combinatorial optimization problems appearing in a wide - riety of industrial, economic, and scienti?c domains. Prominent examples of metaheuristics are evolutionary algorithms, tabu search, simulated annealing, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, ant colony optimization and estimation of distribution algorithms. Problems solved successfully include scheduling,timetabling,networkdesign,transportationanddistribution,vehicle routing, the travelling salesman problem, packing and cutting, satis?ability and general mixed integer programming. EvoCOP began in 2001 and has been held annually since then. It is the ?rst event speci?cally dedicated to the application of evolutionary computation and related methods to combinatorial optimization problems. Originally held as a workshop,EvoCOPbecameaconferencein2004.Theeventsgaveresearchersan excellent opportunity to present their latest research and to discuss current - velopments and applications. Following the general trend of hybrid metaheur- tics and diminishing boundaries between the di?erent classes of metaheuristics, EvoCOPhas broadenedits scope in recent years and invited submissions on any kind of metaheuristic for combinatorial optimization.

The 4th IAPR TC3 Workshop on Arti?cial Neural Networks in Pattern Rec- nition, ANNPR 2010, was held at Nile University (Egypt), April 11-13, 2010. The workshop was organized by the Technical Committee on Neural Networks and Computational Intelligence (TC3) that is one of the 20 technical comm- tees (TC) of the International Association for Pattern Recognition (IAPR). The scope of TC3 includes computational intelligence approaches, such as fuzzy s- tems, evolutionary computing and arti?cial neural networks and their use in various pattern recognition applications. The major topics of ANNPR are supervised and unsupervised learning, f- ture selection, pattern recognition in signal and image processing, and appli- tions in data mining or bioinformatics. High quality across such a diverse ?eld of research is achieved through a rigorous and selective review process. For this workshop, 42 papers were submitted and 23 of them were selected for inc- sion in the proceedings. The workshop was enriched by three invited talks given by Barbara Hammer, University of Bielefeld, Germany, Amir F. Atiya, Cairo University, Egypt, and Mohamed Kamel, University of Waterloo, Canada. We would like to thank all authors for the e?ort they put into their subm- sions, and the Scienti?c Committee for taking the time to provide high-quality reviews and selecting the best contributions for the ?nal workshop program. Special thanks are due to the members of the Nile University Organizing C- mittee,AhmedSalah,AmiraElBaroudy,EsraaAly,HebaEzzat,NesrineSameh, Rana Salah and Mohamed Zahhar for their indispensable contributions to the registration management and local organization.

A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empirical feature space, and the effect of model selection by cross-validation; Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Explores incremental training based batch training and active-set training methods, and decomposition techniques for linear programming SVMs; Discusses variable selection for support vector regressors.

In its lucky 12+1 edition, during April 7-9, 2010, the European Conference on Genetic Programming (EuroGP) travelled to its most easterly location so far, theEuropeanCityof Culture2010,Istanbul,Turkey.EuroGPisthe onlyconf- enceworldwideexclusivelydevotedtogeneticprogrammingandtheevolutionary generation of computer programs. For over a decade, genetic programming (GP) has been considered the new form of evolutionary computation. With nearly 7,000 articles in the online GP bibliography maintained by William B. Langdon, we can say that it is now a mature ?eld. EuroGP has contributed to the success of the ?eld substantially, by being a unique forum for expressing new ideas, meeting, and starting up collaborations. The wide rangeoftopics in this volume re?ectthecurrentstateof researchin the ?eld, including representations, theory, operators and analysis, novel m- els, performance enhancements, extensions of genetic programming,and various applications. The volume contains contributions in the following areas: - Understanding GP behavior andGP analysis include articles on cro- over operators and a new way of analyzing results. -GPperformance presents work on performance enhancements through phenotypic diversity, simpli?cation, ?tness and parallelism. - Novel models and their application present innovative approaches with arti?cial biochemical networks, genetic regulatory networks and geometric di?erential evolution. - Grammatical evolution introduces advances in crossover, mutation and phenotype-genotype maps in this relatively new area. - Machine learning and data mining include articles that present data miningormachinelearningsolutionsusingGPandalsocombinedatamining and machine learning with GP. - Applications rangefromsolvingdi?erentialequations,routingproblems to ?le type detection, object-oriented testing, agents. This year we received 48 submissions, of which 47 were sent to the reviewers.

These proceedings are a record of the Multiple Classi?er Systems Workshop, MCS 2010, held at the Nile University, Egypt in April 2010. Being the ninth in a well-established series of meetings providing an international forum for d- cussion of issues in multiple classi?er system design, the workshop achieved its objective of bringing together researchers from diverse communities (neural n- works, pattern recognition, machine learning and statistics) concerned with this researchtopic.Frommorethan50submissions, theProgramCommitteeselected 31 papers to create an interesting scienti?c program.Paperswere organizedinto sessionsdealingwithclassi?ercombinationandclassi?erselection, diversity, b- ging and boosting, combination of multiple kernels, and applications. The wo- shopprogramandthisvolumewereenrichedbytwoinvitedtalksgivenbyGavin Brown(University of Manchester, UK), and Friedhelm Schwenker(University of Ulm, Germany). As usual, the workshop would not have been possible without the help of many individuals and organizations. First of all, our thanks go to the members of the MCS 2010 Program Committee, whose expertise and dedication helped us create an interesting event that marks the progressmade in this ?eld overthe last year and aspire to chart its future research. The help of James Field from the University of Surrey, who administered the submitted paper reviews, and of Giorgio Fumera who managed the MCS website deserve a particular mention. Special thanks are due to the members of the Nile University Organizing C- mittee, AhmedSalah, AmiraElBaroudy, EsraaAly, HebaEzzat, NesrineSameh, Rana Salah and Mohamed Zahhar for their indispensable contributions to the registration management, local organization, and proceedings pre

The development of new-generation micro-manufacturing technologies and systems has revolutionised the way products are designed and manufactured today with a s- nificant impact in a number of key industrial sectors. Micro-manufacturing techno- gies are often described as disruptive, enabling and interdisciplinary leading to the creation of whole new classes of products that were previously not feasible to ma- facture. While key processes for volume manufacture of micro-parts such as mach- ing and moulding are becoming mature technologies, micro-assembly remains a key challenge for the cost-effective manufacture of complex micro-products. The ability to manufacture customizable micro-products that can be delivered in variable volumes within relatively short timescales is very much dependent on the level of development of the micro-assembly processes, positioning, alignment and measurement techniques, gripping and feeding approaches and devices. Micro-assembly has developed rapidly over the last few years and all the pred- tions are that it will remain a critical technology for high-value products in a number of key sectors such as healthcare, communications, defence and aerospace. The key challenge is to match the significant technological developments with a new gene- tion of micro-products that will establish firmly micro-assembly as a mature manuf- turing process. th The book includes the set of papers presented at the 5 International Precision - sembly Seminar IPAS 2010 held in Chamonix, France from the 14th to the 17th February 2010.

This textbook presents mathematical models in bioinformatics and describes biological problems that inspire the computer science tools used to manage the enormous data sets involved. The first part of the book covers mathematical and computational methods, with practical applications presented in the second part. The mathematical presentation avoids unnecessary formalism, while remaining clear and precise. The book closes with a thorough bibliography, reaching from classic research results to very recent findings. This volume is suited for a senior undergraduate or graduate course on bioinformatics, with a strong focus on mathematical and computer science background.

Image analysis is a computational feat which humans show excellence in, in comp- ison with computers. Yet the list of applications that rely on automatic processing of images has been growing at a fast pace. Biometric authentication by face, ?ngerprint, and iris, online character recognition in cell phones as well as drug design tools are but a few of its benefactors appearing on the headlines. This is, of course, facilitated by the valuable output of the resarch community in the past 30 years. The pattern recognition and computer vision communities that study image analysis have large conferences, which regularly draw 1000 parti- pants. In a way this is not surprising, because much of the human-speci?c activities critically rely on intelligent use of vision. If routine parts of these activities can be automated, much is to be gained in comfort and sustainable development. The - search ?eld could equally be called visualintelligence because it concerns nearly all activities of awake humans. Humans use or rely on pictures or pictorial languages to represent, analyze, and develop abstract metaphors related to nearly every aspect of thinking and behaving, be it science, mathematics, philosopy, religion, music, or emotions. The present volume is an introductory textbook on signal analysis of visual c- putation for senior-level undergraduates or for graduate students in science and - gineering. My modest goal has been to present the frequently used techniques to analyze images in a common framework-directional image processing.

Juval Portugali The notion of complex artificial environments (CAE) refers to theories of c- plexity and self-organization, as well as to artifacts in general, and to artificial - vironments, such as cities, in particular. The link between the two, however, is not trivial. For one thing, the theories of complexity and self-organization originated in the "hard" science and by reference to natural phenomena in physics and bi- ogy. The study of artifacts, per contra, has traditionally been the business of the "soft" disciplines in the humanities and social sciences. The notion of "complex artificial environments" thus implies the supposition that the theories of compl- ity and self-organization, together with the mathematical formalisms and meth- ologies developed for their study, apply beyond the domain of nature. Such a s- st position raises a whole set of questions relating to the nature of 21 century cities and urbanism, to philosophical issues regarding the natural versus the artificial, to the methodological legitimacy of interdisciplinary transfer of theories and me- odologies and to the implications that entail the use of sophisticated, state-of-t- art artifacts such as virtual reality (VR) cities and environments. The three-day workshop on the study of complex artificial environments that took place on the island of San Servolo, Venice, during April 1-3, 2004, was a gathering of scholars engaged in the study of the various aspects of CAE.

Clustering is one of the most fundamental and essential data analysis techniques. Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection.

Kogan and his co-editors have put together recent advances in clustering large and high-dimension data. Their volume addresses new topics and methods which are central to modern data analysis, with particular emphasis on linear algebra tools, opimization methods and statistical techniques. The contributions, written by leading researchers from both academia and industry, cover theoretical basics as well as application and evaluation of algorithms, and thus provide an excellent state-of-the-art overview.

The level of detail, the breadth of coverage, and the comprehensive bibliography make this book a perfect fit for researchers and graduate students in data mining and in many other important related application areas.

We are pleased to present this set of peer-reviewed papers from the ?rst MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support. The MICCAI conference has been the ?agship conference for the m- ical imaging community re?ecting the state of the art in techniques of segm- tation, registration, and robotic surgery. Yet, the transfer of these techniques to clinical practice is rarely discussed in the MICCAI conference. To address this gap, we proposed to hold this workshop with MICCAI in London in September 2009. The goal of the workshop was to show the application of content-based retrieval in clinical decision support. With advances in electronic patient record systems, a large number of pre-diagnosed patient data sets are now bec- ing available. These data sets are often multimodal consisting of images (x-ray, CT, MRI), videos and other time series, and textual data (free text reports and structuredclinicaldata). Analyzing thesemultimodalsourcesfordisease-speci?c information across patients can reveal important similarities between patients and hence their underlying diseases and potential treatments. Researchers are now beginning to use techniques of content-based retrieval to search for disea- speci?c information in modalities to ?nd supporting evidence for a disease or to automatically learn associations of symptoms and diseases. Benchmarking frameworks such as ImageCLEF (Image retrieval track in the Cross-Language Evaluation Forum) have expanded over the past ?ve years to include large m- ical image collections for testing various algorithms for medical image retrieval and classi?cation.

We welcome you to the First International Conference on Arts and Technology (ArtsIT 2009), hosted by CSIE of the National Ilan University and co-organized by the National Science Council, ICST, College of EECS at National Ilan University, Software Simulation Society in Taiwan, ISAC, TCA, NCHC, CREATE-NET, and Institute for Information Industry. ArtsIT2009 was held in Yilan, Taiwan, during September 24-25, 2009. The conference comprised the following themes: * New Media Technologies (Evolutionary systems that create arts or display art works, such as tracking sensors, wearable computers, mixed reality, etc. ) * Software Art (Image processing or computer graphics techniques that create arts, including algorithmic art, mathematic art, advanced modeling and rend- ing, etc. ) * Animation Techniques (2D or 3D computer animations, AI-based animations, etc. ) * Multimedia (Integration of different media, such as virtual reality systems, audio, performing arts, etc. ) * Interactive Methods (Vision-based tracking and recognition, interactive art, etc. ) The conference program started with an opening ceremony, followed by three keynote speeches and four technical sessions distributed over a period of two days. Two poster sessions, one hour each, were scheduled before the afternoon oral sessions. An Int- active Arts Exhibition was held in conjunction with ArtsIT 2009. Twelve well-known digital arts teams from Taiwan exhibited 15 artworks in this event, including 10 int- active installation arts, 4 video arts, and 1 digital print. The conference received around 50 submissions from 15 different countries.